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Exact simulation of noncircular or improper complex-valued stationary Gaussian processes using circulant embedding

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Exact simulation of noncircular or improper complex-valued stationary Gaussian processes using circulant embedding. / Sykulski, Adam M.; Percival, Donald B.
2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings. IEEE Computer Society, 2016. 7738840.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Sykulski, AM & Percival, DB 2016, Exact simulation of noncircular or improper complex-valued stationary Gaussian processes using circulant embedding. in 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings., 7738840, IEEE Computer Society, 26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings, Vietri sul Mare, Salerno, Italy, 13/09/16. https://doi.org/10.1109/MLSP.2016.7738840

APA

Sykulski, A. M., & Percival, D. B. (2016). Exact simulation of noncircular or improper complex-valued stationary Gaussian processes using circulant embedding. In 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings Article 7738840 IEEE Computer Society. https://doi.org/10.1109/MLSP.2016.7738840

Vancouver

Sykulski AM, Percival DB. Exact simulation of noncircular or improper complex-valued stationary Gaussian processes using circulant embedding. In 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings. IEEE Computer Society. 2016. 7738840 doi: 10.1109/MLSP.2016.7738840

Author

Sykulski, Adam M. ; Percival, Donald B. / Exact simulation of noncircular or improper complex-valued stationary Gaussian processes using circulant embedding. 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings. IEEE Computer Society, 2016.

Bibtex

@inproceedings{676a269502cd41938513ceca662828ae,
title = "Exact simulation of noncircular or improper complex-valued stationary Gaussian processes using circulant embedding",
abstract = "This paper provides an algorithm for simulating improper (or noncircular) complex-valued stationary Gaussian processes. The technique utilizes recently developed methods for multi-variate Gaussian processes from the circulant embedding literature. The method can be performed in O(n log2 n) operations, where n is the length of the desired sequence. The method is exact, except when eigenvalues of prescribed circulant matrices are negative. We evaluate the performance of the algorithm empirically, and provide a practical example where the method is guaranteed to be exact for all n, with an improper fractional Gaussian noise process.",
keywords = "Circulant embedding, complex-valued, fractional Gaussian noise, improper, noncircular",
author = "Sykulski, {Adam M.} and Percival, {Donald B.}",
year = "2016",
month = nov,
day = "8",
doi = "10.1109/MLSP.2016.7738840",
language = "English",
booktitle = "2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings",
publisher = "IEEE Computer Society",
note = "26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings ; Conference date: 13-09-2016 Through 16-09-2016",

}

RIS

TY - GEN

T1 - Exact simulation of noncircular or improper complex-valued stationary Gaussian processes using circulant embedding

AU - Sykulski, Adam M.

AU - Percival, Donald B.

PY - 2016/11/8

Y1 - 2016/11/8

N2 - This paper provides an algorithm for simulating improper (or noncircular) complex-valued stationary Gaussian processes. The technique utilizes recently developed methods for multi-variate Gaussian processes from the circulant embedding literature. The method can be performed in O(n log2 n) operations, where n is the length of the desired sequence. The method is exact, except when eigenvalues of prescribed circulant matrices are negative. We evaluate the performance of the algorithm empirically, and provide a practical example where the method is guaranteed to be exact for all n, with an improper fractional Gaussian noise process.

AB - This paper provides an algorithm for simulating improper (or noncircular) complex-valued stationary Gaussian processes. The technique utilizes recently developed methods for multi-variate Gaussian processes from the circulant embedding literature. The method can be performed in O(n log2 n) operations, where n is the length of the desired sequence. The method is exact, except when eigenvalues of prescribed circulant matrices are negative. We evaluate the performance of the algorithm empirically, and provide a practical example where the method is guaranteed to be exact for all n, with an improper fractional Gaussian noise process.

KW - Circulant embedding

KW - complex-valued

KW - fractional Gaussian noise

KW - improper

KW - noncircular

U2 - 10.1109/MLSP.2016.7738840

DO - 10.1109/MLSP.2016.7738840

M3 - Conference contribution/Paper

AN - SCOPUS:85002180279

BT - 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings

PB - IEEE Computer Society

T2 - 26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings

Y2 - 13 September 2016 through 16 September 2016

ER -